U.S. patent number 11,064,937 [Application Number 17/145,661] was granted by the patent office on 2021-07-20 for method and device for in-home sleep and signal analysis.
This patent grant is currently assigned to Cleveland Medical Devices Inc.. The grantee listed for this patent is Cleveland Medical Devices Inc.. Invention is credited to Craig A. Frederick, Hani Kayyali, Brian Kolkowski, Christian Martin, Robert N. Schmidt.
United States Patent |
11,064,937 |
Kayyali , et al. |
July 20, 2021 |
Method and device for in-home sleep and signal analysis
Abstract
The present invention provides a method of conducting a sleep
analysis by collecting physiologic and kinetic data from a subject,
preferably via a wireless in-home data acquisition system, while
the subject attempts to sleep at home. The sleep analysis,
including clinical and research sleep studies and cardiorespiratory
studies, can be used in the diagnosis of sleeping disorders and
other diseases or conditions with sleep signatures, such as
Parkinson's, epilepsy, chronic heart failure, chronic obstructive
pulmonary disorder, or other neurological, cardiac, pulmonary, or
muscular disorders. The method of the present invention can also be
used to determine if environmental factors at the subject's home
are preventing restorative sleep.
Inventors: |
Kayyali; Hani (Shaker Heights,
OH), Frederick; Craig A. (Solon, OH), Martin;
Christian (Eden, NC), Schmidt; Robert N. (Ft. Myers,
FL), Kolkowski; Brian (Leroy, OH) |
Applicant: |
Name |
City |
State |
Country |
Type |
Cleveland Medical Devices Inc. |
Cleveland |
OH |
US |
|
|
Assignee: |
Cleveland Medical Devices Inc.
(Cleveland, OH)
|
Family
ID: |
1000005331563 |
Appl.
No.: |
17/145,661 |
Filed: |
January 11, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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16233520 |
Dec 27, 2018 |
10925535 |
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15229242 |
Oct 1, 2019 |
10426399 |
|
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11811156 |
Jun 8, 2007 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B
5/389 (20210101); A61B 5/398 (20210101); A61B
5/0022 (20130101); A61B 5/0205 (20130101); A61B
5/4815 (20130101); A61B 5/318 (20210101); A61B
5/0077 (20130101); A61B 5/6814 (20130101); A61B
5/369 (20210101); A61B 5/6828 (20130101); A61B
5/14552 (20130101); A61B 5/1135 (20130101); A61B
2560/0242 (20130101); A61B 5/085 (20130101); A61B
2505/07 (20130101); A61B 5/087 (20130101) |
Current International
Class: |
A61B
5/00 (20060101); A61B 5/0205 (20060101); A61B
5/369 (20210101); A61B 5/398 (20210101); A61B
5/389 (20210101); A61B 5/318 (20210101); A61B
5/113 (20060101); A61B 5/087 (20060101); A61B
5/085 (20060101); A61B 5/1455 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Primary Examiner: Jian; Shirley X
Attorney, Agent or Firm: Kolkowski; Brian
Government Interests
The U.S. Government has a paid-up license in this invention and the
right in limited circumstances to require the patent owner to
license others on reasonable terms provided for by the terms of
grant numbers 2R44NS042451-04 and 5R44NS042451-03 awarded by the
National Institutes of Health.
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATIONS
This application claims priority as a continuation of U.S. patent
application Ser. No. 16/233,520, which was filed on Dec. 27, 2018
and which is a continuation of U.S. patent application Ser. No.
15/229,242, which was filed on Aug. 5, 2016 and which issued as
U.S. Pat. No. 10,426,399 on Oct. 1, 2019, and which is a
continuation of U.S. patent application Ser. No. 11/811,156 filed
on Jun. 8, 2007.
Claims
What we claim is:
1. A system for conducting a remote sleep analysis of a subject
comprising: a) a nasal cannula or facemask adapted to be applied to
a subject for measuring airflow of the subject; b) a respiratory
effort belt adapted to be applied to a subject for measuring
respiratory effort of the subject; c) a fingertip pulse oximeter
adapted to be applied to a subject, for measuring blood oxygenation
of the subject; d) a portable patient interface box adapted for
being connected to each of the nasal cannula or facemask,
respiratory effort belt, and fingertip pulse oximeter, the portable
interface box comprising: i. a battery, ii. a processor adapted for
collecting, measuring, and digitizing data corresponding to the
airflow, respiratory effort, and blood oxygenation of the subject,
iii. a non-volatile digital memory adapted to receive and store the
collected data from the processor, iv. a first pressure transducer,
v. a first air port adapted for connecting the nasal cannula or
facemask to the first pressure transducer, vi. a transceiver
adapted for transferring the collected data from the non-volatile
memory, vii. a sensor input adapted to electrically connect the
fingertip pulse oximeter, viii. a second pressure transducer, and
ix. a second air port adapted for connecting the respiratory effort
belt to the second pressure transducer; e) a database that is
remote from the subject, the database adapted for receiving the
collected data transferring from the transceiver; f) at least one
software stored on computer readable storage media and executed by
a computing device, the software when executed is adapted for
analyzing at least part of the data from the database to identify
and draw attention to physiological or technological events
indicative of a sleeping disorder; and g) the at least one software
when executed is further adapted for outputting at least: i. the
transferred collected data, ii. the identified physiological and
technological events, or iii. both (i) and (ii) so as to make a
determination of whether the subject suffers from a sleeping
disorder.
2. The system in claim 1, wherein the portable patient interface
box is adapted to be connected to at least one of the respiratory
effort belt, the fingertip pulse oximeter, or nasal cannula or
facemask before or after application of the sensors to the
subject.
3. The system in claim 1, wherein the portable patient interface
box is adapted to be connected to one of the respiratory effort
belt, the fingertip pulse oximeter, or nasal cannula or facemask
before application of the sensors to the subject.
4. The system in claim 1, wherein the software when executed is
adapted to further perform an automatic scoring of the collected
data to determine whether the subject suffers from a sleeping
disorder.
5. The system in claim 4, wherein the patient interface box
includes a kinetic sensor adapted for measuring body position or
orientation, the processor adapted for collecting, measuring,
digitizing and sending data from the kinetic sensor to the
non-volatile digital memory.
6. The system in claim 5, wherein the system is adapted for
conducting an at-home, sleep analysis of a subject.
7. The system in claim 5, wherein the software when executed is
further adapted to at least in part remove or identify movement
artifacts in the collected data prior to the processor analysis of
the collected data by using an algorithm for comparing data
measured from the kinetic sensor with data measured from an
additional kinetic or physiological sensor to identify and/or
remove movement artifacts.
8. The system in claim 4, wherein the software when executed is
further adapted to at least in part remove or identify movement
artifacts in the collected data prior to the processor analysis of
the collected data by using an algorithm for comparing data
measured from a first kinetic sensor with data measured from a
second kinetic or physiological sensor to identify and/or remove
movement artifacts.
9. The system in claim 1, wherein the processor is further adapted
for checking the adequacy of the collected data from the sensors
prior to transferring the collected data to the database.
10. The system in claim 1, wherein the transceiver is further
adapted to transfer the collected data from the nonvolatile digital
memory via cellular systems, Internet, satellite, wired-network
and/or land lines to the database.
11. The system in claim 1, wherein the database is adapted to
collect and store information for determining whether the subject
being analyzed for a sleep disorder has maintained a normal
sleeping pattern prior to the analysis based on subjective input
from the subject or polysomnography data.
12. The system in claim 1, wherein the patient interface box is
adapted to provide for two way communication between the subject or
their care provider and a sleep technician at a remote
location.
13. A system for conducting an at-home sleep analysis comprising:
a) at least three sensors adapted to be applied to a subject, the
at least three sensors comprising a nasal cannula or facemask, a
respiratory effort belt and a fingertip pulse oximeter, the
respiratory effort belt for measuring respiratory effort of the
subject, the nasal cannula or facemask for measuring airflow of the
subject, and the pulse oximeter for measuring oxygenation of the
subject; b) a portable patient interface box adapted to be worn by
the subject on their torso while the subject attempts to sleep at
home and for connecting the at least three sensors before or after
application of the at least three sensors to the subject, the
portable interface box comprising: i. a battery, ii. at least one
kinetic sensor adapted for measuring body position or orientation,
iii. a nonvolatile digital memory, iv. a pressure transducer, v. an
air port adapted for connecting the nasal cannula or facemask to
the pressure transducer within the portable patient interface box,
vi. a processor adapted for collecting, measuring, digitizing and
storing collected data to the nonvolatile digital memory from the
airflow, the respiratory effort, the blood oxygenation and body
position of the subject during sleep at home, vii. a transceiver
adapted for transferring the collected data from the non-volatile
memory of the portable patient interface box, and viii. releasable
connector sensor inputs electrically connecting-the respiratory
effort belt and the fingertip pulse oximeter; c) a database remote
from the home of the subject, the database adapted for receiving
the collected data from the non-volatile memory transferred by the
transceiver on the portable patient interface box; d) at least one
software stored on computer readable storage media and executed by
a computing device, the software when executed is adapted for
analyzing the transferred collected data from the database to
identify and draw attention to physiological or technological
events indicative of a sleeping disorder; and e) the at least one
software when executed is further adapted for outputting at a
minimum: i) the transferred collected data, ii) the identified
physiological and technological events, or iii) both i) and ii) so
as to make a determination of whether the subject suffers from a
sleeping disorder.
14. The system in claim 13, wherein the processor is further
adapted for checking the adequacy of the collected data from the
sensors prior to transferring the collected data to the
database.
15. The system in claim 13, wherein the transceiver is further
adapted to transfer the collected data from the nonvolatile digital
memory via cellular systems, Internet, satellite, wired-network
and/or land lines to the database.
16. The system in claim 13, wherein the database is adapted to
collect and store information for determining whether the subject
being analyzed for a sleep disorder has maintained a normal
sleeping pattern prior to the analysis based on subjective input
from the subject or polysomnography data.
17. The system in claim 13, wherein the software when executed is
adapted to further perform an automatic scoring of the collected
data to determine whether the subject suffers from a sleeping
disorder.
18. The system in claim 17, wherein the software when executed is
further adapted to at least in part remove or identify movement
artifacts in the collected data prior to the processor analysis of
the collected data by using an algorithm for comparing data
measured from the at least one kinetic sensor with data measured
from an additional kinetic or physiological sensor to identify
and/or remove movement artifacts.
19. The system in claim 13, wherein the patient interface box is
adapted to provide for two way communication between the subject or
their care provider and a sleep technician at the remote location.
Description
BACKGROUND OF THE INVENTION
Nearly one in seven people in the United States suffer from some
type of chronic sleep disorder, and only 50% of people are
estimated to get the recommended seven to eight hours of sleep each
night. It is further estimated that sleep deprivation and its
associated medical and social costs (loss of productivity,
industrial accidents, etc.) exceed $150 billion dollars per year.
Excessive sleepiness can deteriorate the quality of life and is a
major cause of morbidity and mortality due to its role in
industrial and transportation accidents. Sleepiness further has
undesirable effects on motor vehicle driving, employment, higher
earning and job promotion opportunities, education, recreation, and
personal life.
Primary sleep disorders affect approximately 50 million Americans
of all ages and include narcolepsy, restless legs/periodic leg
movement, insomnia, and most commonly, obstructive sleep apnea
(OSA). OSA's prevalence in society is comparable with diabetes,
asthma, and the lifetime risk of colon cancer. OSA is grossly under
diagnosed; an estimated 80-90% of persons afflicted have not
received a clinical diagnosis. Secondary sleep disorders include
loss of sleep due to pain associated with chronic infections,
neurological/psychiatric disorders, or alcohol/substance abuse
disorders.
Sleeping disorders are currently diagnosed by two general methods.
Subjective methods, such as the Epworth and Standford Sleepiness
Scale, generally involve questionnaires that require patients to
answer a series of qualitative questions regarding their sleepiness
during the day. With these subjective methods, however, it is found
that the patients usually underestimate their level of sleepiness
or they deliberately falsify their responses because of their
concern regarding punitive action or as an effort to obtain
restricted stimulant medication.
The second group of methods uses physiological evaluations, such as
all-night polysomnography to evaluate a patient's sleep
architecture (e.g., obtaining respiratory disturbance index to
diagnose sleep apnea). A polysomnogram (PSG) can also be followed
by an all-day test such as the Multiple Sleep Latency Test (MSLT)
or its modified version, the Maintenance of Wakefulness Test (MWT).
The PSG typically requires patients to spend the night in a sleep
laboratory connected to multiple sensors while they attempt to
sleep. Because it is conducted in a lab setting, a PSG cannot
provide information about a patient's sleeping environment, such as
noise, light, or allergens. A PSG also can be difficult to conduct
because of a patient's travel concerns or anxiety related to
sleeping away from home. Many patients also exhibit a "first night
effect" related to a change in sleeping environment. The first
night effect often requires a second night in the sleep lab to
obtain accurate results. Therefore, the first night effect can
easily double the cost of conducting a PSG in a sleep lab.
To combat the difficulties of conducting a PSG in a sleep lab,
various methods have been employed to attempt to conduct a PSG test
in a patient's home. The systems used in these methods have not
been capable of transmitting data. Therefore, these systems have
only allowed unattended PSG tests. These methods involve storage of
the data to a computer hard disc or other media for the duration of
the test. After the test is completed, the media is received, read,
and analyzed. Obtaining the data creates an additional delay
between completion of the test and the final diagnosis that is not
present for a lab-based PSG. Further, unattended tests are plagued
with signal failure. In one study involving unattended home PSG,
data from over 23% of the patients were unusable due to missing
channels, even though a technician called the PSG recording device
every 30 minutes to check the quality of the recordings.
None of the current methods for conducting a PSG at home allow
transmission of the collected data during the test. All of the
current methods require the PSG data to be stored during the test
and read only after the test has been completed. As such, the data
cannot be periodically or continuously checked for adequacy. Even
if the data were periodically evaluated, the current methods do not
use a step of allowing a remote monitor to communicate with the
subject to correct any sensor/signal problems. The current methods
also do not include live video feeds, enabling a remote monitor to
visualize the subject during the test. Because of the lack of data
availability, communication, and video, the current methods of
conducting a PSG at home are by definition unattended sleep
studies. It is therefore an object of the present invention to
provide a method of conducting a sleep analysis at home wherein the
data is transmitted at substantially the same time it that is
collected or created. It is another object of the present invention
to provide a method of conducting a sleep analysis at home that is
remotely attended. It is another object of the present invention to
provide a method of conducting a sleep analysis that includes
information about the patient's sleeping environment, including
environmental factors. It is still another object of the present
invention that this method of conducting a sleep analysis be
inexpensive.
SUMMARY OF THE INVENTION
The present invention provides a method of conducting a sleep
analysis by collecting physiologic and kinetic data from a subject,
preferably via a wireless in-home data acquisition system, while
the subject attempts to sleep at home. The sleep analysis,
including clinical and research sleep studies and cardiorespiratory
studies, can be used in the diagnosis of sleeping disorders and
other diseases or conditions with sleep signatures, such as
Parkinson's, epilepsy, chronic heart failure, chronic obstructive
pulmonary disorder, or other neurological, cardiac, pulmonary, or
muscular disorders. The method of the present invention can also be
used to determine if environmental factors at the subject's home
are preventing restorative sleep.
The method of conducting a sleep study at home includes a number of
steps that enhance this method over other methods presently used.
These features available in various embodiments of the present
invention may include, but are not necessarily limited to: a step
for hooking up the patient with the necessary sensors at the
doctor's office or the home, a step for collecting multiple
channels of data to evaluate a number of physiological, kinetic,
and environmental features of the subject and sleeping location; a
step for including a subject's body motion; a step for using
removable memory for data buffering and storage; a step for
movement artifact correction using video; a step for transmitting
data wirelessly to a remote processing or monitoring station after
a manual or automatic radio frequency (RF) sweep; a step for
remotely checking the data for adequacy; a step for remotely
monitoring the subject via streaming data and audio/video for the
duration of the test; a step for communicating with the subject
during the test; and a step for adjusting electrodes and other
sensors during the test.
The software used in various steps of the present invention allows
the in-home data acquisition system to perform a number of
operations that other systems cannot accomplish with the same type
of hardware. The use of software filtering allows determination of
airflow, tidal volume, ventilation rate, and snore detection from a
single pressure transducer. The use of software also makes many of
the video-related features possible. Software is used to
synchronize video with the other signals for display. Software is
also used to remove data artifacts created by subject movement. The
software corrects motion artifacts by using data acquired from
accelerometers and video.
The present invention may include a step of transmitting data via a
wired network such as a dial-up modem, cellular networks, digital
subscriber lines (DSL), cable broadband, fiber-optic lines,
satellite communications, direct radio, infra-red links, and the
like. The data can be transmitted once, at multiple points during
the test, or continuously. With continuous data transmission, the
sleep test can be remotely monitored from anywhere around the
world. The data furthermore may be monitored by multiple viewing
stations by methods including but not limited to serial
retransmission from one station to another, or simultaneous
transmission by 3-way or conference calling, broadcasting or the
like. The data from the acquisition system is available for remote
monitoring in real time, it can be saved and scored later, or may
be quantitatively analyzed and scored (even automatically) and then
viewed. With automatic or computer-assisted scoring, the software
can alert a individual performing remote monitoring when a
physiological event (such as a drop in oxygen saturation) or a
technological event (such as an electrode becoming disconnected)
occurs.
Various embodiments of the present invention include the step of
applying at least two sensors to the subject. The sensors can be
applied at any location, such as a physician's office or place of
business, or the subject's home or other sleeping location. The
subject's sleeping location includes but is not limited to the
subject's home, apartment, or the like, as well as a hotel, nursing
home, or other location where an individual could sleep and where
this analysis could be done more controllably and/or less
expensively than in an attended sleep lab or hospital setting.
Similarly, the sensors can be applied by a variety of individuals,
including but not limited to a physician, nurse, sleep technician,
or other healthcare professional. Just as preferably, the sensors
could be applied by the subject or the subject's spouse, friend,
roommate, or other individual capable of attaching the various
sensors with guidance and instruction.
In one embodiment, the present invention includes the steps of
applying two or more sensors to a subject; connecting the sensors
to an in-home data acquisition system capable of transmitting the
signals from the sensors or retransmitting a signal based at least
in part on at least one of the signals from the sensors; collecting
signals from the sensors while the subject attempts to sleep at
home; and analyzing the signals to determine whether the subject
has a sleeping disorder. The first and second steps of this (and
every other) embodiment can also be switched, meaning the sensors
are connected to the in-home data acquisition system and then
applied to the subject. The step of collecting data while the
subject attempts to sleep allows for diagnosis of insomnias in
addition to parasomnias and other conditions that manifest while
the subject actually sleeps. Further, it is understood that the
first step of the present invention involving applying two or more
sensors to a subject can be accomplished by applying any
combination of sensors, including two or more EEG electrodes.
Another embodiment of the present invention includes the steps of
applying two or more sensors to a subject; connecting the sensors
to an in-home data acquisition system; collecting signals from the
sensors while the subject attempts to sleep at home; storing the
signals on removable memory; retrieving the signals; and analyzing
the signals to determine whether the subject has a sleeping
disorder. The steps of storing and retrieving the signals allow the
analysis to be completed at a convenient time, rather than
requiring analysis as the data is collected. These steps also allow
the in-home data acquisition system to be reused after the data is
removed with the removable memory, even if the data has not been
viewed or analyzed.
In another embodiment, the present invention includes the steps of
applying two or more sensors to a subject; connecting the sensors
to an in-home data acquisition system; collecting signals from the
sensors while the subject attempts to sleep at home; pre-processing
the signals, for example to remove motion artifacts, and thereby
creating a new signal or signals; and analyzing the original
signals and/or the new signals to determine whether the subject has
a sleeping disorder. The step of pre-processing the signals to
remove motion artifacts improves the quality of the data. For
example, the presence of motion artifact can result in
misdiagnosis, prolong procedure duration, and lead to delayed or
inappropriate treatment decisions. Thus, it is imperative to remove
motion artifacts from the biopotential signal to prevent these
problems from occurring during the sleep analysis.
In another embodiment, the present invention includes the steps of
applying two or more sensors to a subject; setting up a video
camera in the subject's sleeping location; connecting the sensors
and camera to an in-home data acquisition system; collecting
signals from the sensors and camera while the subject attempts to
sleep at home; and analyzing data to determine whether the subject
has a sleeping disorder. The step of using a video camera allows
for monitoring and analysis of the subject's environment. For
example, the use of video can indicate that the subject's
complaints may be related to changes in light levels, sleeping
disorders of the subject's bedmate, frequent tossing and turning
indicative of an unsuitable mattress, coughing or sneezing
indicative of poor air quality or the presence of allergens, pets
sleeping with the subject, and the like.
In another embodiment, the present invention includes the steps of
applying a set of sensors to a subject, the sensors being for two
electroencephalogram (EEG) channels, two electro-oculogram (EOG)
channels, one chin electromyogram (EMG) channel, one nasal airflow
channel, one oral airflow channel, two electrocardiogram (ECG)
channels, one thoracic respiratory effort channel, one abdominal
respiratory effort channel, one pulse oximetry channel, one leg EMG
channel, and one accelerometer; connecting the sensors to a
wireless in-home data acquisition system; collecting signals from
the applied sensors and from additional environmental sensors while
the subject attempts to sleep, the environmental sensors being a
digital infrared video camera, an ambient light sensor, and an
audio channel; pre-processing the signals, for example to remove
motion artifacts and to derive a snore signal; using removable
memory as a buffer to wirelessly transmit the data to a remote
monitoring and/or remote analysis location; evaluating the data to
determine if it is adequate for later diagnosis; storing the data
on a removable memory card; conducting an RF sweep; wirelessly and
continuously transmitting all the data from the physiologic,
kinetic, and environmental sensors to a remote monitoring location;
continuously monitoring the subject from the remote monitoring
location using the continuously transmitted data, including the
video feed; contacting the subject to make any necessary changes to
the test, including but not limited to waking the patient, asking
the patient to adjust sensors, altering the type of sleep test to
focus on certain channels, or stopping the test; using the video
channel to process the data, for example to remove motion artifacts
in the collected signals; and analyzing the data to determine
whether the subject has a sleeping disorder. This embodiment allows
for conducting a complete polysomnogram (PSG) with additional
environmental signals that is virtually or remotely attended. This
embodiment allows replication of a sleep lab PSG with the subject
comfortably at home. Allowing the subject to attempt to sleep at
home eliminates the "first night effect" and provides more accurate
data for the sleep diagnosis because the home PSG method controls
for the subject's sleeping environment. Subjects are also generally
more comfortable sleeping at home and are more willing to
participate in full PSG studies that do not involve traveling to a
sleep lab or sleeping in a new environment.
In yet another embodiment, the present invention includes the steps
of providing a subject with a kit of sensors, an in-home data
acquisition system, and instructions; sending the subject home;
having the subject use the instructions and/or live help (ex.,
telephone or videoconferencing assistance) to apply the physiologic
and kinetic sensors, set up any environmental sensors, and connect
all the sensors to the in-home data acquisition system; collecting
some preliminary data from the subject; wirelessly transmitting the
preliminary data to a remote monitoring or analysis location;
evaluating the data to determine if it is adequate for later
diagnosis; optionally instructing the subject to adjust any sensors
to obtain adequate data; collecting signals from the sensors while
the subject attempts to sleep at home; wirelessly transmitting all
the data to a remote monitoring location; continuously monitoring
the subject from the remote monitoring location; and analyzing the
data to determine whether the subject has a sleeping disorder. The
step of providing the subject with a kit of sensors, an in-home
data acquisition system, and instructions, as well as the step of
having the subject set up the system at home with the availability
of live assistance, allows the subject to participate in a sleep
study without ever leaving home. This embodiment is particularly
useful for homebound individuals, or individuals who live too far
away from a sleep study facility.
In still a further embodiment, the present invention includes the
steps of applying two or more sensors to a subject; connecting the
sensors to an in-home data acquisition system; collecting signals
from the sensors while the subject attempts to sleep at home;
pre-processing the signals, for example to apply a filter or remove
motion artifacts; transmitting the pre-processed physiological
signal at least in part wirelessly to a remote monitor or
processor; and analyzing the data to determine whether the subject
has a sleep disorder.
In still a further embodiment, the present invention includes the
steps of applying two or more sensors to a subject; connecting the
sensors to an in-home data acquisition system; collecting signals
from the sensors while the subject attempts to sleep at home;
filtering the physiological signal; transmitting the filtered
physiological signal wirelessly to a base station; re-transmitting
the filtered physiological signal from the base station to a remote
monitor or processor over telephone lines, fiber optic cable, cable
broadband, satellite communications, and/or a cellular tower; and
analyzing the data to determine whether the subject has a sleep
disorder.
In still a further embodiment, the present invention includes the
steps of applying two or more sensors to a subject; connecting the
sensors to an in-home data acquisition system; collecting signals
from the sensors while the subject attempts to sleep at home;
transmitting to another location the signals or another signal
based at least in part on at least one of the signals from the
sensors applied to the subject at a substantially same time as the
signals are received or created; and analyzing the data to
determine whether the subject has a sleep disorder. The step of
transmitting or retransmitting the signals at a substantially same
time allows real-time analysis of the data, rather than waiting for
the conclusion of the test in order to begin data analysis.
Real-time analysis also enables the individual performing remote
monitoring and analysis to recognize a physiological event (such as
a drop in oxygen saturation, seizure activity, changes in heart
rate, and the like) or a technological event (such as an electrode
becoming disconnected, inappropriate movement of a sensor, and the
like) occurs.
In still a further embodiment, the present invention includes the
steps of applying two or more sensors to a subject; connecting the
sensors to an in-home data acquisition system; collecting signals
from the sensors while the subject attempts to sleep at home;
maintaining the availability of communication between the subject
and a remote monitor for the duration of the test; and analyzing
the data to determine whether the subject has a sleep disorder.
Additional features and advantages of the invention will be set
forth in the detailed description that follows, and in part will be
readily apparent to those skilled in the art from that description
or recognized by practicing the invention as described herein,
including the detailed description that follows, the claims, as
well as the appended drawings.
It is to be understood that both the foregoing general description
and the following detailed description are merely exemplary of the
invention, and are intended to provide an overview or framework for
understanding the nature and character of the invention as it is
claimed. The accompanying drawings are included to provide a
further understanding of the invention, and are incorporated in and
constitute a part of this specification. The drawings illustrate
various embodiments of the invention and together with the
description serve to explain the principles and operation of the
invention.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 Block diagram of one embodiment of the present invention
showing the steps of checking the adequacy of signals and
communicating with the subject.
FIG. 2 Signal flow diagram of one embodiment of the present
invention showing the in-home data acquisition system.
FIG. 3 Schematic representation of one embodiment of the present
invention showing the remote data acquisition method.
FIG. 4 Schematic representation of one embodiment of the present
invention used with a subject to acquire EEG signals from the
subject and then transmit them to the receiver and attached
computer.
FIG. 5 Block diagram of one embodiment of the signal processing
step of the present invention.
FIG. 6 Block diagram of one embodiment of the base station used in
the present invention.
FIG. 7 Schematic representation of one embodiment of the present
invention showing an in-home data acquisition system of multiple
interface boxes used on a single subject, wherein the interface
boxes are transmitting to a single receiver.
FIG. 8 Block diagram of one embodiment of the present invention
showing the motion artifact rejection process.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
The present invention is related to a method of home sleep and
signal analysis, particularly electroencephalogram (EEG) signal
analysis. The present invention is further related to the devices
used in executing the method. The present invention includes
various embodiments of a method of home sleep analysis. These
embodiments include but are not limited to one or more of the
following steps.
Various embodiments of the present invention include a step for
determining whether the subject being analyzed for a sleep disorder
maintained a normal sleeping pattern prior to the analysis. This
step can be performed or accomplished a number of ways. In the
simplest form, the subject can be questioned regarding his or her
previous sleep patterns. In a somewhat more complex form the
subject can be requested to fill out a questionnaire, which then
can be graded to determine whether his or her previous sleep
patterns where normal (or appeared normal). In an even more complex
form the subject might undergo all night polysomnography to
evaluate the subject's sleep architecture (e.g., obtaining
respiratory disturbance index to diagnose sleep apnea). One of the
objectives of this step is to ensure that the results of the
subject's brain wave analysis are not the result of or affected by
the subject's previous environmental factors i.e., intentional lack
of sleep, etc. It is clear that there are numerous ways beyond
those examples previously mentioned of determining whether the
subject being analyzed maintained or thought they were maintaining
a normal sleeping pattern prior to analysis, therefore the examples
given above are included as exemplary rather than as a limitation,
and those ways of determining whether the subject maintained or
thought they were maintaining a normal sleeping pattern known to
those skilled in the art are considered to be included in the
present invention.
Various embodiments of the present invention include the step of
conducting an at-home sleep analysis that is attended from a remote
location. Such remote attendance can be accomplished by an
individual in a remote location (a remote monitor) periodically or
continuously viewing the data transmitted from the in-home data
acquisition system, including signals from the sensors applied to
the subject, signals from the environmental sensors, and a
pre-processed signal or signals based at least in part on at least
one of the sensors.
The preferred embodiment of secure data transmission that is
compatible with HIPAA and HCFA guidelines will be implemented using
a virtual private network. More preferably, the virtual private
network will be implemented using a specialized security appliance,
such as the PIX 506E, from Cisco Systems, Inc, capable of
implementing IKE and IPSec VPN standards using data encryption
techniques such as 168-bit 3DES, 256-bit AES, and the like. Still
more preferably, secure transmission will be provided by a 3.sup.rd
party service provider or by the healthcare facility's information
technology department. The system will offer configuration
management facilities to allow it to adapt to changing guidelines
for protecting patient health information (PHI).
Preferably, the data includes a video channel. Preferably, the
remote monitor is capable of communicating with the subject,
subject's assistant, or other individual near the subject. Such
communication allows the remote monitor to provide instructions to
the subject, subject's assistant, or other individual near the
subject, for example, to adjust a sensor, close window blinds,
remove a source of noise, or wake the subject. More preferably, the
remote monitor is capable of two-way communication with the
subject, subject's assistant, or other individual near the subject.
Such communication allows the subject, subject's assistant, or
other individual close to the subject to ask the remote monitor
questions, for example, to clarify instructions.
Various embodiments of the present invention include the step of
applying at least two sensors to the subject. The sensors can be
applied at any location. Preferably, the sensors are applied in a
physician's office or place of business. The physician's place of
business includes but is not limited to an office building, a
freestanding sleep center, location within a hospital, mobile
vehicle or trailer, leased space, or similar location. Just as
preferably, the sensors could be applied in the subject's home or
other sleeping location. The subject's sleeping location includes
but is not limited to the subject's home, apartment, and the like,
as well as a hotel, nursing facility, or other location where an
individual could sleep and where this analysis could be done more
controllably and/or less expensively than in a sleep lab or
hospital setting. Similarly, the sensors can be applied by a
variety of individuals, including but not limited to a physician,
nurse, sleep technician, or other healthcare professional. Just as
preferably, the sensors could be applied by the subject or the
subject's spouse, friend, roommate, or other individual capable of
attaching the various sensors. More preferably, the sensors could
be applied by the subject or the subject's spouse, friend,
roommate, or other individual capable of attaching the various
sensors with guidance and instruction. Such guidance and
instruction can include static information such as pamphlets, audio
recordings (on cassettes, compact discs, and the like), video
recordings (on videocassettes, digital video discs, and the like),
websites, and the like, as well as dynamic information such as
direct real-time communication via telephone, cell phone,
videoconference, and the like.
The sensors that are used with various embodiments of the present
invention are described herein but can also be any of those known
to those skilled in the art for the applications of this method.
The collected physiological, kinetic, and environmental signals can
be obtained by any method known in the art. Preferably, those
sensors include, but are not limited, to wet or dry electrodes,
photodetectors, accelerometers, pneumotachometers, strain gauges,
thermal sensors, pH sensors, chemical sensors, gas sensors (such as
oxygen and carbon dioxide sensors), transducers, piezo sensors,
magnetometers, pressure sensors, static charge-sensitive beds,
microphones, audio monitors, video monitors, and the like. The
invention is envisioned to include those sensors subsequently
developed by those skilled in the art to detect these types of
signals. For example, the sensors can be magnetic sensors. Because
electro-physiological signals are, in general, electrical currents
that produce associated magnetic fields, the present invention
further anticipates methods of sensing those magnetic fields to
acquire the signal. For example, new magnetic sensors could collect
brain wave signals similar to those that can be obtained through a
traditional electrode applied to the subject's scalp.
Various embodiments of the present invention include a step for
applying sensors to the subject. This step can be performed or
accomplished in a number of ways. In the simplest form, two sensors
are applied to the subject to measure a single channel of
physiologic or kinetic data. In a somewhat more complex form,
multiple sensors are applied to the subject to collect data
sufficient for a full PSG test. The preferred set of sensors for
PSG testing includes sensors for two EEG channels, one EOG
channels, one chin EMG channel, one nasal airflow channel, one oral
airflow channel, one ECG channel, one thoracic respiratory effort
channel, one abdominal respiratory effort channel, one pulse
oximetry channel, and one shin or leg EMG channel. More preferably,
the minimal set of PSG sensors is augmented with at least one
additional channel of EOG, one channel of body position (ex., an
accelerometer), one channel of video, and optionally one channel of
audio. In an even more complex form, many sensors are applied to
the subject to collect full PSG data as well as additional
physiological, kinetic, and environmental data. For example,
additional EEG electrodes may be applied to the subject to rule out
seizure disorders, an esophageal pH sensor may be used to detect
acid reflux, and a hygrometer or photometer may be used to detect
ambient humidity or light, respectively. The set of sensors can be
two sensors. More preferably, four sensors are used. Still more
preferably five sensors; still more preferably seven sensors; still
more preferably ten sensors; still more preferably twelve sensors;
still more preferably fifteen sensors; still more preferably
twenty-four sensors.
Electro-physiological signals such as EEG, ECG, EMG, EOG,
electroneurogram (ENG), electroretinogram (ERG), and the like can
be collected via electrodes placed at one or several relevant
locations on the subject's body. For example when measuring brain
wave or EEG signals, electrodes may be placed at one or several
locations on the subject's scalp. In order to obtain a good
electro-physiological signal, it is desirable to have low
impedances for the electrodes. Typical electrodes placed on the
skin may have an impedance in the range of from 5 to 10 k.OMEGA..
It is in generally desirable to reduce such impedance levels to
below 2 k.OMEGA.. A conductive paste or gel may be applied to the
electrode to create a connection with an impedance below 2
k.OMEGA.. Alternatively or in conjunction with the conductive gel,
a subject's skin may be mechanically abraded, the electrode may be
amplified, or a dry electrode may be used. Dry physiological
recording electrodes of the type described in U.S. Pat. No.
7,032,301 are herein incorporated by reference. Dry electrodes are
advantageous because they use no gel that can dry out, skin
abrasion or cleaning is unnecessary, and the electrode can be
applied in hairy areas such as the scalp. Additionally if
electrodes are used as the sensors, preferably at least two
electrodes are used for each channel of data--one signal electrode
and one reference electrode. Optionally, a single reference
electrode may be used for more than one channel.
When electrodes are used to collect EEG or brain wave signals,
common locations for the electrodes include frontal (F), parietal
(P), mastoid process (A), central (C), and occipital (O).
Preferably for the present invention, when electrodes are used to
collect EEG or brain wave data, at least one electrode is placed in
the occipital position and referenced against an electrode placed
on the mastoid process (A). More preferably, when electrodes are
used to collect EEG or brain wave data, electrodes are placed to
obtain a second channel of data from the central location. If
further EEG or brain wave signal channels are desired, the number
of electrodes required will depend on whether separate reference
electrodes or a single reference electrode is used.
If electrodes are used to collect cardiac signals using an ECG,
they may be placed at specific points on the subject's body. The
ECG is used to measure the rate and regularity of heartbeats,
determine the size and position of the heart chambers assess any
damage to the heart, and diagnose sleeping disorders. An ECG is
important as a tool to detect the cardiac abnormalities that can be
associated with respiratory-related disorders.
As the heart undergoes depolarization and repolarization,
electrical currents spread throughout the body because the body
acts as a volume conductor. The electrical currents generated by
the heart are commonly measured by an array of twelve electrodes
placed on the arms, legs, and chest. Although a full ECG test
typically involves twelve electrodes, only two are required for
many tests such as a sleep study. When electrodes are used to
collect ECG with the present invention, preferably only two
electrodes are used. When two electrodes are used to collect ECG,
preferably one is placed on the subject's left-hand ribcage under
the armpit, and the other preferably on the right-hand shoulder
near the clavicle bone. Optionally, a full set of twelve ECG
electrodes may be used, such as if the subject is suspected to have
a cardiac disorder. The specific location of each electrode on a
subject's body is well known to those skilled in the art and varies
between both individuals and types of subjects. If electrodes are
used to collect ECG, preferably the electrode leads are connected
to a device contained in the signal processing module of the
in-home data acquisition system used in the present invention that
measures potential differences between selected electrodes to
produce ECG tracings.
The two basic types of ECG leads are bipolar and unipolar. Bipolar
leads (standard limb leads) have a single positive and a single
negative electrode between which electrical potentials are
measured. Unipolar leads (augmented leads and chest leads) have a
single positive recording electrode and use a combination of the
other electrodes to serve as a composite negative electrode. Either
type of lead is acceptable for collecting ECG signals in the
present invention.
Other sensors can be used to measure various parameters of a
subject's respirations. Measurement of airflow is preferably
measured using sensors or devices such as a pneumotachometer,
strain gauges, thermal sensors, transducers, piezo sensors,
magnetometers, pressure sensors, static charge-sensitive beds, and
the like. These sensors or devices also preferably measure nasal
pressure, respiratory inductance plethysmography, thoracic
impedance, expired carbon dioxide, tracheal sound, snore sound,
blood pressure and the like. Measurement of respiratory effort is
preferably measured by a respiration belt, esophageal pressure,
surface diaphragmatic EMG, and the like. Measurement of oxygenation
and ventilation is preferably measured by pulse oximetry,
transcutaneous oxygen monitoring, transcutaneous carbon dioxide
monitoring, expired end carbon dioxide monitoring, and the
like.
One example of such a sensor for measuring respirations either
directly or indirectly is a respiration belt. Respiration belts can
be used to measure a subject's abdominal and/or thoracic expansion
over a measurement time period. The respiration belts may contain a
strain gauge, a pressure transducer, or other sensors that can
indirectly measure a subject's respirations and the variability of
respirations by providing a signal that correlates to the
thoracic/abdominal expansion/contractions of the subject's
thoracic/abdominal cavity. If respiration belts are used, they may
be placed at one or several locations on the subject's torso or in
any other manner known to those skilled in the art. Preferably,
when respiration belts are used, they are positioned below the
axilla and/or at the level of the umbilicus to measure rib cage and
abdominal excursions. More preferably, at least two belts are used,
with one positioned at the axilla and the other at the
umbilicus.
Another example of a sensor or method for measuring respirations
either directly or indirectly is a nasal cannula or a facemask used
to measure the subject's respiratory airflow. Nasal or oral airflow
can be measured quantitatively and directly with a pneumotachograph
consisting of a pressure transducer connected to either a standard
oxygen nasal cannula placed in the nose or a facemask over the
subject's mouth and nose. Airflow can be estimated by measuring
nasal or oral airway pressure that decreases during inspiration and
increases during expiration. Inspiration and expiration produce
fluctuations on the pressure transducer's signal that is
proportional to airflow. A single pressure transducer can be used
to measure the combined oral and nasal airflow. Alternatively, the
oral and nasal components of these measurements can be acquired
directly through the use of at least two pressure transducers, one
transducer for each component. Preferably, the pressure
transducer(s) are internal to the interface box. If two transducers
are used for nasal and oral measurements, preferably each has a
separate air port into the interface box.
Software filtering can obtain "snore signals" from a single
pressure transducer signal by extracting the high frequency portion
of the transducer signal. This method eliminates the need for a
separate sensor, such as a microphone or another transducer, and
also reduces the system resources required to detect both snore and
airflow. A modified nasal cannula or facemask connected to a carbon
dioxide or oxygen sensor may be used to measure respective
concentrations of these gases. In addition, a variety of other
sensors can be connected with either a nasal cannula or facemask to
measure a subject's respirations directly or indirectly.
Still another example of a sensor or method of directly or
indirectly measuring respirations of the subject is a pulse
oximeter. The pulse oximeter can measure the oxygenation of the
subject's blood by producing a source of light at two wavelengths
(650 nm and 905, 910, or 940 nm). Hemoglobin partially absorbs the
light by amounts that differ depending on whether it is saturated
or desaturated with oxygen. Calculating the absorption at the two
wavelengths leads to an estimate of the proportion of oxygenated
hemoglobin. Preferably, pulse oximeters are placed on a subject's
earlobe or fingertip. More preferably, the pulse oximeter is placed
on the subject's index finger. In one embodiment of the present
invention, a pulse oximeter is built-in or hard-wired to the
interface box. Alternatively, the pulse oximeter can be a separate
unit in communication with either the interface box or the base
station via either a wired or wireless connection.
Kinetic data can be obtained by accelerometers placed on the
subject. Alternatively, several accelerometers can be placed in
various locations on the subject, for example on the wrists, torso,
and legs. These accelerometers can provide both motion and general
position/orientation data by measuring gravity. A video signal can
also provide some kinetic data after processing. Alternatively,
stereo video signals can provide three-dimensional position and
motion information. Kinetic data includes but is not limited to
frequent tossing and turning indicative of an unsuitable mattress,
excessive movement of bedding indicating unsuitable sleeping
temperatures, and unusual movement patterns indicating pain.
Environmental data can be collected by video cameras, microphones
(to detect noise level, etc.), photodetectors, light meters,
thermal sensors, particle detectors, chemical sensors, mold
sensors, olfactory sensors, barometers, hygrometers, and the like.
Environmental data can provide insight into the subject's sleeping
location and habits that is unavailable in the traditional
laboratory setting. Environmental data can indicate that the
subject's sleeping location is a potential source of the subject's
sleeping difficulty. By way of example, but not limitation,
environmental data can indicate that the subject's sleeping
location has an unsuitable temperature, humidity, light level,
noise level, or air quality. For example, these environmental
conditions can cause sweating, shivering, sneezing, coughing,
noise, and/or motion that disrupts the patient's sleep. The
environmental sensors can be placed anywhere in the subject's
sleeping location or on the subject, if appropriate. Preferably,
the environmental sensors are placed near, but not necessarily on,
the subject.
Other sensors can be used to measure various parameters of a
subject's physiological, kinetic, or environmental conditions.
These other parameters are preferably measured using sensors or
devices such as a photodetectors, light meters, accelerometers,
pneumotachometers, strain gauges, thermal sensors, pH sensors,
chemical sensors, transducers, piezo sensors, magnetometers,
pressure sensors, static charge-sensitive beds, audio monitors,
microphones, reflective markers, video monitors, hygrometers, and
the like. Because the system is programmable, potentially any
transducer-type sensor that outputs an electrical signal can be
used with the system.
Various embodiments of the present invention include the step of
connecting the applied sensors to an in-home data acquisition
system. The sensors can be connected to the in-home data
acquisition system either before or after they are applied to the
subject. As an example of connecting the sensors to the in-home
data acquisition system after the sensors are applied to the
subject, a physician can apply the sensors to the subject and then
send the subject home. While at home, the subject can connect the
applied sensors to the in-home data acquisition system.
Alternatively, the sensors can be connected to the in-home data
acquisition system and then applied to the subject.
The sensors can be permanently hardwired to at least part of the
in-home data acquisition system. More preferably, the sensors are
connected to at least part of the in-home data acquisition system
via releasable connector. The physiological sensors are generally
hardwired (permanently or via releasable connector) to the in-home
data acquisition system, but the ongoing evolution in wireless
sensor technology may allow sensors to contain transmitters.
Optionally, such sensors are wirelessly connected to the in-home
data acquisition system. As such, these sensors and the wireless
connection method are considered to be part of the present
invention. With the advances in microelectromechanical systems
(MEMS) sensor technology, the sensors may have integrated analog
amplification, integrated A/D converters, and integrated memory
cells for calibration, allowing for some signal conditioning
directly on the sensor before transmission.
Preferably, the sensors are all connected in the same way at the
same time, although this is certainly not required. It is possible,
but less preferable, to connect the sensors with a combination of
methods (i.e., hardwired or wireless) at a combination of times
(i.e., some before application to the subject, and some after
application to the subject).
Various embodiments of the present invention use an in-home data
acquisition system. The in-home data acquisition system is
preferably portable. By portable, it is meant, among other things,
that the device is capable of being transported relatively easily.
Relative ease in transport means that the device is easily worn and
carried, generally in a carrying case, to the point of use or
application and then worn by the subject without significantly
affecting any range of motion. Furthermore, any components of the
in-home data acquisition system that are attached to or worn by the
subject, such as the sensors and patient interface box, should also
be lightweight. Preferably, these patient-contacting components of
the device (including the sensors and the patient interface box)
weigh less than about 10 lbs., more preferably less than about 7.5
lbs., even more preferably less than about 5 lbs., and most
preferably less than about 2.5 lbs. Thus, the patient-contacting
components of the device preferably are battery-powered and use a
data storage memory card and/or wireless transmission of data,
allowing the subject to be untethered. Furthermore, the entire
in-home data acquisition system (including the patient-contacting
components as well as any environmental sensors, base station, or
other components) preferably should be relatively lightweight. By
relatively lightweight, it is meant preferably the entire in-home
data acquisition system, including all components such as any
processors, computers, video screens, cameras, and the like
preferably weigh less in total than about 20 lbs., more preferably
less than about 15 lbs., and most preferably less than about 10
lbs. This in-home data acquisition system preferably can fit in a
reasonably sized carrying case so the patient or assistant can
easily transport the system. By being lightweight and compact, the
device should gain greater acceptance for use by the subject.
While the equipment and methods used in the various embodiments of
the present invention can be used in rooms or buildings adjacent to
the subject's sleeping location, due to the equipment's robust
nature these methods are preferably performed over greater
distances. Preferably, the subject's sleeping location and the
remote locations, for example the location of the remote monitor,
are separate buildings. Preferably, the subject's sleeping location
is at least 1 mile from the remote location(s) receiving the data;
more preferably, the subject's sleeping location is at least 5
miles from the remote location(s) receiving the data; even more
preferably, the subject's sleeping location is at least twenty
miles from the remote location(s) receiving the data; still more
preferably, the subject's sleeping location is at least fifty miles
from the remote location(s) receiving the data; still even more
preferably, the subject's sleeping location is at least two
hundred-fifty miles from the remote location(s) receiving the data;
more preferably, the subject's sleeping location is in a different
state from the remote location(s) receiving the data; and most
preferably, the subject's sleeping location is in a different
country from the remote location(s) receiving the data.
Various embodiments of the present invention use an in-home data
acquisition system capable of receiving signals from the sensors
applied to the subject and capable of retransmitting the signals or
transmitting another signal based at least in part on at least one
of the signals. In its simplest form, the in-home data acquisition
system preferably should interface with the sensors applied to the
subject and retransmit the signals from the sensors. Preferably,
the in-home data acquisition system wirelessly transmits the
signals from the sensors. Optionally, the in-home data acquisition
system also pre-processes the signals from the sensors and
transmits the pre-processed signals. Further optionally, the data
acquisition is also capable of storing the signals from the sensors
and/or any pre-processed signals.
Optionally, the in-home data acquisition system can be a single box
containing a sensor interface module, a pre-processor module, and a
transmitter module. Further optionally, the in-home data
acquisition system could consist of several boxes that communicate
with each other, each box containing one or more modules. For
example, the data acquisition could consist of (a) a patient
interface box containing a sensor interface module, a
pre-processor, a transmitter, and a receiver; and (b) a base
station box containing a second pre-processor, a transmitter, and a
receiver. In this example, the transmitter and receiver of the
patient box are used to communicate with the base station box. The
transmitter and receiver of the base station box are used to both
communicate with the patient box and a remote monitoring station,
remote analysis station, remote data storage station, and the like.
Similarly, the data acquisition could consist of (a) a patient
interface box containing a sensor interface module, a transmitter,
and a receiver; (b) a processor box containing a pre-processor, a
transmitter, and a receiver; and (c) a base station box containing
only a receiver and a transmitter. In these configurations, it is
not necessary for the transmitters to be of the same type. For
example, the transmitter in the patient interface box can be a
wired or Bluetooth transmitter, and the transmitter in the base
station box can be a WiFi or IEEE 802.11 transmitter designed to
establish connections over larger distances.
Various embodiments of the present invention use an in-home data
acquisition system capable of storing and/or retransmitting the
signals from the sensors or storing and/or transmitting another
signal based at least in part on at least one of the signals. The
in-home data acquisition system can be programmed to send all
signal data to the removable memory, to transmit all data, or to
both transmit all data and send a copy of the data to the removable
memory. When the in-home data acquisition system is programmed to
store a signal or pre-processed signal, the signals from the
sensors can be saved on a medium in order to be retrieved and
analyzed at a later date. Media on which data can be saved include,
but are not limited to chart recorders, hard drive, floppy disks,
computer networks, optical storage, solid-state memory, magnetic
tape, punch cards, etc. Preferably, data are stored on removable
memory. For both storing and transmitting or retransmitting data,
flexible use of removable memory can either buffer signal data or
store the data for later transmission. Preferably, nonvolatile
removable memory can be used to customize the system's buffering
capacity and completely store the data.
If the in-home data acquisition system is configured to transmit
the data, the removable memory acts as a buffer. In this situation,
if the in-home data acquisition system loses its connection with
the receiving station, the in-home data acquisition system will
temporarily store the data in the removable memory until the
connection is restored and data transmission can resume. If however
the in-home data acquisition system is configured to send all data
to the removable memory for storage, then the system does not
transmit any information at that time. In this situation, the data
stored on the removable memory can be retrieved by either
transmission from the in-home data acquisition system, or by
removing the memory for direct reading.
The method of directly reading will depend on the format of the
removable memory. Preferably the removable memory is easily
removable and can be removed instantly or almost instantly without
tools. The memory is preferably in the form of a card and most
preferably in the form of a small easily removable card with an
imprint (or upper or lower surface) area of less than about two sq.
in. If the removable memory is being used for data storage,
preferably it can write data as fast as it is produced by the
system, and it possesses enough memory capacity for the duration of
the test. These demands will obviously depend on the type of test
being conducted, tests requiring more sensors, higher sampling
rates, and longer duration of testing will require faster write
speeds and larger data capacity. The type of removable memory used
can be almost any type that meets the needs of the test being
applied. Some examples of the possible types of memory that could
be used include but are not limited to Flash Memory such as
CompactFlash, SmartMedia, Miniature Card, SD/MMC, Memory Stick, or
xD-Picture Card. Alternatively, a portable hard drive, CD-RW
burner, DVD-RW burner or other data storage peripheral could be
used. Preferably, a SD/MMC--flash memory card is used due to its
small size. A PCMCIA card is least preferable because of the size
and weight.
When the in-home data acquisition system is programmed to
retransmit the signals from the sensors, preferably the in-home
data acquisition system transmits the signals to a processor for
analysis. More preferably, the in-home data acquisition system
immediately retransmits the signals to a processor for analysis.
Optionally, the in-home data acquisition system receives the
signals from one or more of the aforementioned sensors and stores
the signals for later transmission and analysis. Optionally, the
in-home data acquisition system both stores the signals and
immediately retransmits the signals.
When the in-home data acquisition system is programmed to
retransmit the signals from the sensors or transmit a signal based
at least in part on the signal from the sensors (collectively "to
transmit" in this section), the in-home data acquisition system can
transmit through either a wireless system, a tethered system, or
some combination thereof. When the system is configured to transmit
data, preferably the data transmission step utilizes a two-way
(bi-directional) data transmission. Using two-way data transmission
significantly increases data integrity. By transmitting redundant
information, the receiver (the processor, monitoring station, or
the like) can recognize errors and request a renewed transmission
of the data. In the presence of excessive transmission problems,
such as transmission over excessive distances or obstacles
absorbing the signals, the in-home data acquisition system can
control the data transmission or independently manipulate the data.
With control of data transmission it is also possible to control or
re-set the parameters of the system, e.g., changing the
transmission channel or encryption scheme. For example, if the
signal transmitted is superimposed by other sources of
interference, the receiving component could secure a flawless
transmission by changing the channel. Another example would be if
the transmitted signal is too weak, the receiving component could
transmit a command to increase the transmitting power. Still
another example would be for the receiving component to change the
data format of the transmission, e.g., in order to increase the
redundant information in the data flow. Increased redundancy allows
easier detection and correction of transmission errors. In this
way, safe data transmissions are possible even with the poorest
transmission qualities. This technique opens a simple way to reduce
the transmission power requirements, thereby reducing the energy
requirements and providing longer battery life. Another advantage
of a bi-directional digital data transmission lies in the
possibility of transmitting test codes in order to filter out
external interferences, for example, refraction or scatter from the
transmission current. In this way, it is possible to reconstruct
falsely transmitted data.
Several preferable embodiments of this method employ a wireless
in-home data acquisition system. This wireless in-home data
acquisition system consists of several components, each wirelessly
connected. Data is collected from the sensors described above by a
patient interface box. The patient interface box then wirelessly
transmits the data to a separate signal pre-processing module,
which then wirelessly transmits the pre-processed signal to a
receiver. Alternatively, the patient interface box processes the
signal and then directly transmits the processed signal directly to
the receiver using wireless technology. Further alternatively, the
patient interface box wirelessly transmits the signals to the
receiver, which then pre-processes the signal. Preferably, the
wireless technology used by the in-home data acquisition system
components is radio frequency based. Most preferably, the wireless
technology is digital radio frequency based. The signals from the
sensors and/or the pre-processed signals are transmitted wirelessly
to a receiver, which can be a base station, a transceiver hooked to
a computer, a personal digital assistant (PDA), a cellular phone, a
wireless network, or the like. Most preferably, the physiological
signals are transmitted wirelessly in digital format to a
receiver.
Wireless signals between the wireless in-home data acquisition
system components are both received and transmitted via frequencies
preferably less than about 2.0 GHz. More preferably, the
frequencies are primarily 902-928 MHz, but Wireless Medical
Telemetry Bands (WMTS), 608-614 MHz, 1395-1400 MHz, or 1429-1432
MHz can also be used. The present invention may also use other less
preferable frequencies above 2.0 GHz for data transmission,
including but not limited to such standards as Bluetooth, WiFi,
IEEE 802.11, and the like.
When a component of the wireless in-home data acquisition system is
configured to wirelessly transmit data, it is preferably capable of
conducting a RF sweep to detect an occupied frequency or possible
interference. The system is capable of operating in either "manual"
or "automatic" mode. In the manual mode, the system conducts an RF
sweep and displays the results of the scan to the system monitor.
The user of the system can then manually choose which frequency or
channel to use for data transmission. In automatic mode, the system
conducts a RF sweep and automatically chooses which frequencies to
use for data transmission. The system also preferably employs a
form of frequency hopping to avoid interference and improve
security. The system scans the RF environment then picks a channel
over which to transmit based on the amount of interference
occurring in the frequency range.
The receiver (base station, remote communication station, or the
like) of various embodiments of the wireless in-home data
acquisition system can be any device known to receive RF
transmissions used by those skilled in the art to receive
transmissions of data. By way of example but not limitation, the
receiver can include a communications device for relaying the
transmission, a communications device for re-processing the
transmission, a communications device for re-processing the
transmission then relaying it to another remote communication
station, a computer with wireless capabilities, a PDA with wireless
capabilities, a processor, a processor with display capabilities,
and combinations of these devices. Optionally, the receiver can
further transmit data to another device and/or back. Further
optionally, two different receivers can be used, one for receiving
transmitted data and another for sending data. For example, with
the wireless in-home data acquisition system used in the present
invention, the receiver can be a wireless router that establishes a
broadband Internet connection and transmits the physiological
signal to a remote Internet site for analysis, preferably by the
subject's physician or another clinician. Other examples of a
receiver are a PDA, computer, or cell phone that receives the data
transmission, optionally re-processes the information, and
re-transmits the information via cell towers, land phone lines, or
cable to a remote processor or remote monitoring site for analysis.
Other examples of a receiver are a computer or processor that
receives the data transmission and displays the data or records it
on some recording medium that can be displayed or transferred for
analysis at a later time.
Preferably, the in-home data acquisition system retransmits the
signals from the sensors applied to the subject or transmits a
signal based at least in part on at least one of the physiological,
kinetic, or environmental signals at substantially a same time as
the signal is received or generated. At substantially the same time
preferably means within approximately one hour. More preferably, at
substantially the same time means within thirty minutes. Still more
preferably, at substantially the same time means within ten
minutes. Still more preferably, at substantially the same time
means within approximately one minute. Still more preferably, at
substantially the same time means within milliseconds of when the
signal is received or generated. Most preferably, a substantially
same time means that the signal is transmitted or retransmitted at
a nearly instantaneous time as it is received or generated.
Transmitting or retransmitting the signal at substantially a same
time allows the physician or monitoring service to review the
subject's physiological and kinetic signals and the environmental
signals and if necessary to make a determination, which could
include modifying the patient's treatment protocols or asking the
subject to adjust the sensors.
Various embodiments of the present invention include a step of
monitoring a patient from a separate monitoring location. Data
transmitted in a remote monitoring application may include, but are
not limited to, physiological data, kinetic data, environmental
data, audio, and/or video recording. It is preferable that both
audio and video communications be components of the envisioned
system in order to provide interaction between patient and
caregiver.
The envisioned remote monitoring step will require data processing,
storage, and transmission. This step may be completed or
accomplished in one or more modules of the in-home data acquisition
system. The preferred embodiment realizes the remote system as two
separate components with a patient interface module that can
collect, digitize, store, and transmit data to a base station
module that can store, process, compress, encrypt, and transmit
data to a remote monitoring location.
Preferably, the data is transmitted from a base station to a
database or remote monitoring location with a wireless module or
card through a cellular service provider. The envisioned remote
monitoring application may allow for multiple remote monitoring
locations anywhere in the world. Remote data collection to
monitoring station configurations may include, but are not limited
to one-to-one, one-to-many, many-to-one, or many-to-many. The
envisioned system may include a central server, or group of servers
that can collect data from one or more remote sites and offer
delivery to multiple viewing clients.
It is preferable that the remote monitoring application employ a
wireless network link between the patient and caregiver such as a
cellular wireless network. Other wireless techniques include but
are not limited to satellite communications, direct radio, infrared
links, and the like. Data transmission through a wired network such
as dial-up modem, digital subscriber line (DSL), or fiber-optic,
while less preferable, can also be used. Bandwidth management
facilities will be employed to facilitate remote monitoring in
low-speed communication networks. Several data compression
techniques are envisioned to maximize system utilization in
low-bandwidth environments.
Data compression using lossless encoding techniques can provide
basic throughput optimization, while certain lossy encoding
techniques will offer far greater throughput while still providing
useful data. Lossy encoding techniques may include but are not
limited to decimation, or transmission of a compressed image of the
data. The preferred method for encoding will include special
processing from the transmitter that will preprocess the data
according to user-selectable options, such as digital filtering,
and take into the account the desired visual representation of that
information, such as pixel height and target image width.
Facilities can be made within the system to control the encoding in
order to optimize utilization on any given network. Control over
the encoding methods may include, but is not limited to selection
of a subset of the entire set of signals, target image size, and
decimation ratio.
Data encryption can be applied to secure data transmissions over
any network. Encryption methods may include but are not limited to
simple obfuscation and sophisticated ciphers.
The preferred embodiment of the aforementioned remote monitoring
system (a form of the in-home data acquisition system) will consist
of several system modules. A patient interface module will collect
physiological and kinetic data and transmit them to a base station
module. The base station module will receive the physiological and
kinetic data from the patient module, and will also directly
connect to the environmental sensors. The base station module will
consist of an embedded computer equipped with a cellular wireless
data/voice card and a night-vision video acquisition system. The
embedded computer will collect, analyze, compress, and encrypt the
data and relay them to one or more viewing caregivers. The remote
monitoring systems will broadcast their dynamically assigned IP
addresses to a dedicated address server, which will be used for
lookup by the viewing caregivers. Computer software used by
caregivers will enumerate each remote monitoring system in the
field using the aforementioned address server and allow caregivers
to select one or more for monitoring. The software will have the
ability to control data acquisition including start and stop of
acquisition, as well as system reconfiguration.
The software will also provide real-time control over the display
of data including page width, amplitude, color, montage, and the
like. The software will also provide both real-time video and audio
communication with the patient using dual services from the
cellular card. Video will preferably be transmitted through the
data connection, and audio will preferably be transmitted through
the voice connection.
Signal quality of the signals from all the sensors can be affected
by the posture and movement of the subject. For methods of the
present invention, it is important to reduce motion artifacts from
the sensor placement. Errors in the form of noise can occur when
biopotential data acquisition is performed on a subject. For
example, a motion artifact is noise that is introduced to a
biopotential signal via motion of an electrode placed on the skin
of a subject. A motion artifact can also be caused by bending of
the electrical leads connected to any sensor. The presence of
motion artifacts can result in misdiagnosis, prolong procedure
duration and can lead to delayed or inappropriate treatment
decisions. Thus, it is imperative to remove motion artifact from
the biopotential signal to prevent these problems from occurring
during treatment.
The present method of collecting signals from a subject includes a
means of reducing motion artifacts. Preferably, the electrode
sensors are used with conductive gels or adhesives. More
preferably, dry electrodes are used with or without conductive gels
or adhesives. Still more preferably, the device's firmware and/or
software uses body motion information for artifact correction. Most
preferably, a combination of the above methods is used.
The most common methods for reducing the effects of motion
artifacts in sensors such as electrodes have focused on skin
deformation. These methods include removing the upper epidermal
layer of the skin by abrasion, puncturing the skin near the
electrode, or measuring skin stretch at the electrode site. The
methods for skin abrasion ensure good electrical contact between
the electrode and the subject's skin. In this method, an abrasive
pad is mechanically rotated on the skin to abrade the skin surface
before electrode placement. Moreover, medical electrodes have been
used with an abrading member to prepare the skin after application
of the electrode whereby an applicator gun rotates the abrading
member. Methods of skin preparation that abrade the skin with a
bundle of fibers have also been disclosed. The methods discussed
above provide a light abrasion of the skin to reduce the electrical
potential and minimize the impedance of the skin, thereby reducing
motion artifacts.
Skin abrasion methods can cause unnecessary subject discomfort,
prolong procedure preparation time and can vary based on operator
experience. Furthermore, skin abrasions methods can lead to
infection, and do not provide an effective solution to long term
monitoring. Dry physiological recording electrodes could be used as
an alternative to gel electrodes. Dry physiological recording
electrodes of the type described in U.S. Pat. No. 7,032,301 are
herein incorporated by reference. Dry physiological electrodes do
not require any of the skin abrasion techniques mentioned above and
are less likely to produce motion artifacts in general.
Although the above-mentioned methods reduce motion artifacts, they
do not completely eliminate them. The invention preferably
incorporates a step to more completely remove motion and other
artifacts by firmware and/or software correction that utilizes
information collected preferably from a sensor or device to detect
body motion, and more preferably from an accelerometer. In certain
embodiments of the present invention, a 3-D accelerometer is
directly connected to the in-home data acquisition system. The
in-home data acquisition system receives signal inputs from the
accelerometer and at least one set of other physiological or
kinetic signals. The microprocessor applies particular tests and
algorithms comparing the two signal sets to correct any motion
artifacts that have occurred. The processor in one embodiment
applies a time synchronization test, which compares the at least
one set of physiological or kinetic signal data to the
accelerometer signal data synchronized in time to detect motion
artifacts and then remove those artifacts. Alternatively, the
processor may apply a more complicated frequency analysis.
Frequency analysis preferably in the form of wavelet analysis can
be applied to the accelerometer and at least one set of
physiological or kinetic signals to yield artifact detection. Yet
another alternative is to create a neural net model to improve
artifact detection and rejection. This allows for the system to be
taught over time to detect and correct motion artifacts that
typically occur during a test study. The above examples are only
examples of possible embodiments of the present invention and are
not limitations. The accelerometer data need not be analyzed before
wireless transmission; it could be transmitted analyzed by a base
station, computer, or the like after transmission. As should be
obvious to those skilled in the art, a 2-D accelerometer or an
appropriate array of accelerometers could also be used. Gyroscopes
could be used as well for these purposes.
Sensors can be used to detect motion of the subject's body or a
portion of the subject's body. The motion information can then be
used to detect the posture and movement of the subject and to
correct for error in the form of noise or motion artifact in the
other sensor channels. To detect motion, various embodiments of the
present invention include sensors, devices, and methods of
determining the posture and movement of the subject. This
information can be used when analyzing the physiological signals.
The posture and movement of the subject is preferably determined by
signals received from an accelerometer or an array of two or more
accelerometers. Accelerometers are known in the art and are
suitable for use as motion-monitoring units. Various other types of
sensors can be additionally or alternatively used to sense the
criteria (e.g., vibration, force, speed, and direction) used in
determining motion. For particularly low power designs, the one or
more sensors used can be largely mechanical.
Body movement of the subject will result in a high amplitude signal
from the accelerometer. The in-home data acquisition system can
also monitor the sensor signals for any indication that the subject
has moved, for example from a supine position to an upright
position. For example, the integrated velocity signal computed from
the vertical acceleration component of the sensor data can be used
to determine that the subject has just stood up from a chair or sat
up in bed. A sudden change in the vertical signal, particularly
following a prolonged period with little activity while the subject
is sleeping or resting, confirms that a posture-changing event
occurred.
In addition, a video camera can be used to detect subject movement
and position, and the information then used to correct any
artifacts that may have arisen from such movement. Preferably, the
camera is a digital camera. More preferably, the camera is a
wireless digital camera. Still more preferably, the camera is a
wireless digital infrared camera. Preferably, the video acquired
from the camera is processed so that the subject's movement and
position are isolated from other information in the video. The
movement and position data that are acquired from the video is then
preferably analyzed by software algorithms. This analysis will
yield the information needed to make artifact corrections of the
physiological signals.
One specific embodiment of the present invention using video
subject movement detection involves the use of specially marked
electrodes. The electrodes can be any appropriate electrode known
in the art. The only change to the electrode is that they
preferably have predetermined high contrast marks on them to make
them more visible to the video camera. These marking could be
manufactured into the electrodes or simply be a sticker that is
placed on the back of the electrodes. These markings enable the
video system to accurately distinguish the electrodes from the rest
of the video image. Using the markers on each visible electrode,
the system can calculate of the movement of each individual
electrode, thus allowing for more accurate artifact correction.
In another specific embodiment of the invention, the system can
detect subject movement by monitoring the actual movement of the
subject's body. Software is applied to the video that first
isolates the position of the subject's body, including limbs, and
then continues to monitor the motion of the subject.
There are numerous advantages to using video over other means of
artifact detection and correction. Foremost, video allows for the
calculation of movement artifacts from each individual electrode
without the need for accelerometers. This makes the use of video
very cost effective in relation to other available methods. The
video also can be used in conjunction with the accelerometer data
to correct for motion artifacts, thus increasing the precision and
accuracy of the system's motion artifact correction
capabilities.
Various embodiments of the present invention include the step of
pre-processing the signals received from the sensors attached to
the subject. The processor or pre-processor of various embodiments
of the present invention can be independent, a part of the
interface box, or a part of the base station. Optionally,
pre-processing can correct artifacts, derive a snore signal, filter
a signal, or compress and/or encrypt the data for transmission,
each as described above. Preferably, the preprocessing step
corrects for artifacts present in the sensor signals.
Various embodiments of the present invention include the step of
analyzing the received signals to determine if the patient has a
sleeping disorder. This step can be performed or accomplished a
number of ways. In one form, a sleep technician or other trained
individual scores the sleep test in accordance with Rechtschaffen
and Kales (R&K) criteria. Another form uses a standard MSLT
analysis. Still another form involves automatic or
computer-assisted scoring of the data. The analysis step can
include a full R&K score, or specific features can be targeted.
For example, in cases of suspected sleep-related breathing
disorders, the analysis can focus on detecting and classifying
respiratory events. Any analysis method used to diagnose sleeping
disorders (including but not limited to insomnia, excessive daytime
sleepiness, parasomnias, restless leg syndrome, periodic limb
movement disorder, and sleep-disordered breathing such as apneas)
based on physiological and/or kinetic data collected while the
subject attempts to sleep is an appropriate means of completing
this step. Analysis can also include subjective information from
the subject, such as the subject's response to questions. Such
questions include, but are not limited to, standard subjective
questionnaires such as the Epworth and Standford Sleepiness Scale,
and asking if the subject slept well.
The analysis can occur after receipt of the entire data set. More
preferably, the analysis can take place in near-real time as the
data are received. Still more preferably, the analysis is
computer-assisted and takes place in near-real time. Alternatively,
the data can be partially analyzed, with or without computer
assistance, in near-real time, and then fully analyzed at a later
time. If at least some of the analysis is conducted in near-real
time with computer assistance, the analysis software can provide an
alert signal to draw attention to a physiological or technological
event. Physiological events include, but are not limited to,
changes in blood oxygen saturation, changes in pulse, changes in
sleep stage, and subject movement, such as leaving the bed.
Technological events include, but are not limited to, movement of a
sensor, changes in electrode impedance, or loss of data. Once
alerted to a physiological or technological event, the remote
monitor can take action, including but not limited to communicating
with the subject to address a problem, making a note of the event,
conducting more detailed analysis, altering the test parameters, or
alerting another individual such as a physician, nurse, sleep
technician, or the subject's assistant.
Various embodiments of the present invention include the step of
evaluating the received signals to determine if they are adequate
for later analysis. This step can be performed or accomplished a
number of ways. In the simplest form, the signal can be evaluated
once just prior to the start of the sleep study. In another form,
the signal is evaluated periodically during the study to determine
its quality. Preferably, the signal(s) are evaluated both at the
start of the study and periodically during the study. Most
preferably, the signals are evaluated at the beginning of the study
and continuously during the study. If the signals are evaluated for
adequacy, preferably the subject can be contacted to adjust the
sensor as necessary. In this way, corrective action can adjust an
inadequate signal to increase the value of the sleep study data and
enable later analysis.
By transmitting the data wirelessly in this application it is meant
that the data at least in part of the data transfer process is
transmitted wirelessly. This means for example that the data may be
transmitted wirelessly from the patient data acquisition box to the
base station and then sent via wireless cellular card, internet,
through the testing facilities LAN, or any other communication
system. This also means for example that the data may be
transmitted directly from the patient data acquisition box through
a wireless cellular card then over the internet to a database which
distributes the data over a hardwired system to the sleep unit or
lab. This also means for example that the data may be transmitted
directly from the patient data acquisition box with a wireless WIFI
card directly to a wireless network then over the internet to a
processor which retransmits the processed data to the sleep unit or
laboratory. Preferably, the patient data acquisition box, however,
needs to wirelessly transmit the data. This allows for a simplified
patient hookup and improved patient mobility.
The data collected for the sleep analysis conducted under the
various methods of the present invention can be viewed by any
number of medical personnel and the patient themselves, if
appropriate. Preferably, the data is available to a sleep
technician, to a doctor making the analysis/diagnosis based on the
data, and others involved in these methods. This data can be
reviewed at multiple locations including but not limited to the
doctor's home or office, or anywhere else the doctor or other
individuals associated with the analysis/diagnosis have access to
the internet or a intranet.
FIG. 1 is a block diagram of one embodiment of the sleep analysis
method of the present invention showing, among other things, the
steps of checking the adequacy of signals and communicating with
the subject. In this embodiment, a physician, nurse, technician, or
the like applies sensors to the subject 2 at the physician's office
or place of business. The subject is sent home 4 with an in-home
data acquisition system. At home, the subject or the subject's
assistant connects the sensors to the in-home data acquisition
system 6. The in-home data acquisition system collects some data
from the sensors and transmits the data to a remote station 8. At
the remote station, a remote monitor checks the signals for
adequacy 10. If the signal is not adequate for later analysis 12,
the remote monitor communicates with the subject to adjust the
sensor 14. After the subject adjusts the sensor as instructed by
the remote monitor, the in-home data acquisition system collects
and transmits more data to the remote monitoring station 8. The
signal from the adjusted sensor is checked for adequacy 10. The
signal check loop 8, 10, 12, 14 is repeated until the signals from
the sensors are adequate for later analysis.
After the in-home data acquisition system is sending adequate
signals 12, the sleep test is started by collecting data while the
subject attempts to sleep at home 16. During the test, data is
collected and transmitted to the remote monitoring station 18.
Based on the transmitted data, a sleep analysis is performed and
the patient is diagnosed 20.
FIG. 2 is a signal flow diagram of one embodiment of the data flow
through the wireless in-home data acquisition system used in
certain embodiments of the present invention. The sensors generate
physiological signals 22, kinetic signals 24, and environmental
signals 26. The sensor signals 27 interface with the wireless
in-home data acquisition system 50, consisting of (a) a patient
interface box 35 containing a sensor interface module 28, a
preprocessor module 30, a transceiver module 32, and a power module
34, and (b) a base station 43 containing a storage module 38, a
second pre-processor module 40, and a communication module 42.
Typically, the patient interface box 35 is worn by the subject
during the test period. For portability of the patient interface
box 35, the power module 34 can be battery-based. The patient
interface box 35 sends data via wireless signal 46 to the base
station 43. The base station 43 uses the communication module 42 to
retransmit the signals from the sensors 27 and/or transmit signals
based at least in part on at least one of the signals 27 to remote
stations (not shown). Optionally, environmental signals 26 could be
fed directly into the base station 43. Further optionally, all the
signals 27 could be fed directly into a single box (not shown)
containing the sensor interface module 28, pre-processor module 30,
storage module 38, communication module 42, and power module 34.
Although transmission between the patient interface box 35 and the
base station box 43 is shown in FIG. 2 as wireless 46, the
connection could also be wired in other embodiments of the in-home
data acquisition system.
FIG. 3 is schematic of the remote data acquisition device and
system of the present invention. In FIG. 3, a wireless in-home data
acquisition system 50 (shown in FIG. 2) is used to receive, filter,
and optionally analyze signals 27 (shown in FIG. 2) from sensors
(not shown) on a subject (not shown). The wireless in-home data
acquisition system 50 transmits a signal based, at least in part,
on one or more of the signals from the sensors on the subject. The
in-home data acquisition system 50 transmits a signal 55 preferably
in real time from the subject's home 52 to a server 70 for
analysis. The signal 55 is transmitted over the internet or other
communication system 58. Such other communication systems include
satellites, cellular networks, local area networks (LAN), other
wide area networks (WAN), or other telecommunications system. If
the signal 55 is transmitted over the internet 58, preferably the
signal 55 is transmitted using a cellular card provided by cellular
providers such as for example Sprint, Cingular, AT&T, T-Mobile,
Alltel, Verizon or the like. The signal 55 that is transmitted over
the internet or other communication system 58 can be compressed to
provide better resolution or greater efficiency. The server 70
performs data analysis (not shown). The analyzed data 73 is then
entered into a database 76. The analyzed data 73 in the database 76
is then accessible and can be requested 79 and sent to multiple
review stations 82 anywhere in the world via the internet or other
communications system 58 for further analysis and review by
clinicians, technicians, researchers, doctors and the like. The
communications systems used for data transmission need not be the
same at all stages. For example, the a cellular network can be used
to transmit data between the subject's home 52 and the remote
analysis server 70. Then the internet can be used to transmit data
between the remote analysis server 70 and the database 76. Finally
in this example, a LAN can be used to transmit data between the
database 76 and a review station 82.
FIG. 4 shows a diagram outlining the wireless in-home data
acquisition system in more detail. In FIG. 4, a patient interface
box 85 receives signal (not shown) from a sensor 91. This sensor 91
can be an EEG electrode (as shown) or any of the other sensors
described herein or known in the art. Although one type of sensor
91 is shown, the patient interface box 85 is capable of accepting
multiple signals from multiple sensors 91. In a very simple
embodiment of the present invention, the patient interface box 85
generates a wireless signal 94 encoded with data corresponding to
the signal from the sensor 91. The patient interface box 85
transmits the wireless signal 94 to base station 97. In FIG. 4, the
wireless signal 94 is shown as radio frequency (RF). In this case,
the patient interface box 85 generates a radio frequency signal 94
by frequency modulating a frequency carrier and transmits the radio
frequency signal through module antenna 100. The base station 97
receives the radio frequency signal 94 through base antenna 103,
demodulates the radio frequency signal 94, and decodes the data. It
is understood that other wireless means can be utilized with the
present invention, such as infrared and optical, for example. RF
wireless transmission is preferred. Although one module antenna 100
and one base antenna 103 are shown in this embodiment, it is
understood that two or more types of antennas can be used and are
included in the present invention. An external programming means
106, shown in FIG. 4 as a personal computer, contains software that
is used to program the patient interface box 85 and the base
station 97 through data interface cable 109. The data interface
cable 109 is connected to the base station 97 by connector 112.
Instead of a data interface cable 109, the patient interface box 85
and the base station 97 can be programmed by radio frequency (or
other type) of signals transmitted between an external programming
means 106 and a base station 97 and the patient interface box 85 or
to another base station 97. RF signals, therefore, can be both
transmitted and received by both patient interface box 85 and base
station 97. In this event the patient interface box 85 also
includes a module receiver 133 (shown on FIG. 5) while the base
station 97 also includes a base transmitter 84, in effect making
both the patient interface box 85 and the base station 97 into
transceivers. In addition, the data interface cable 109 also can be
used to convey data from the base station 97 to the external
programming means 106. If a personal computer is the external
programming means 106, it can monitor, analyze, and display the
data in addition to its programming functions. The base receiver 80
and module receiver 133 (shown on FIG. 5) can be any appropriate
receivers, such as direct or single conversion types. The base
receiver 80 preferably is a double conversion superheterodyne
receiver while the module receiver 133 (shown on FIG. 5) preferably
is a single conversion receiver. Advantageously, the receiver
employed will have automatic frequency control to facilitate
accurate and consistent tuning of the radio frequency signal 94
received thereby.
Referring now to FIG. 5, there is shown a block diagram of the
signal processing module 85 with the sensor 91 and the module
antenna 100. The signal processing module 85 comprises input means
115, analog-to-digital (A/D) means 118, a module microcontroller
121 with a nonvolatile memory, advantageously, an EEPROM 124, a
module transmitter 127, a connection to removable memory 130, a
module receiver 133 and a module power supply 136. Although the
module antenna 100 is shown externally located from the signal
processing module 85, it can also be incorporated therein. The
module antenna 100 may be a printed spiral antenna printed on a
circuit board or on the case of the signal processing module 85 or
other type of antenna. A module power supply 136 provides
electrical power to the signal processing module 85 which includes
the input means 115, A/D means 118, module microcontroller 121,
module transmitter 127 and module receiver 133. Additionally the
signal processing module 85 will preferably contain an
accelerometer connected to a microprocessor 139 for position
detection, motion detection, and motion artifact correction.
The input means 115 is adjustable either under control of the
module microcontroller 121 or by means of individually populatable
components based upon the specific external input 88 (i.e. signal
from any sensor) characteristics and range enabling the input means
115 to accept that specific external input 88. For example, if the
input is a 4-20 mA analog signal, the input means 88 is programmed
by the module microcontroller 121 and/or populated with the
components needed to accept that range and characteristic of
signals. If the input characteristics change the programming and/or
components change accordingly but the same platform circuit board
design is utilized. In other words, the same platform design is
utilized notwithstanding the character, range, or quantity (i.e.
number of external inputs 88) [up to a predetermined limit] of the
input. For example, bioelectric signals such as EEG, EMG, EKG, EOG,
or the like have typical amplitudes of a few microvolts up to a few
tens of millivolts. For a given application, a specific frequency
band of interest might be from 0.1 Hz to 100 Hz, whereas another
application may require measurement of signals from 20 Hz to 10
kHz. Alternatively, measurement of vital signs such as body
temperature and respiration rate may deal with signals in a range
of +5 volts, with a frequency content from DC (0 Hz) to 20 Hz. For
other medical applications, the information of interest may be
contained in the signal as a current, current loop sensor, or it
may take the form of resistance, impedance, capacitance,
inductance, conductivity, or some other parameter. The present
invention anticipates using a single device for measuring such
widely disparate signal types and presents distinct economic
advantages, especially to small enterprises such as a medical
clinic located in a rural area, which would be empowered by this
invention to conduct tests that would otherwise require the patient
travel to a large medical center, with all the attendant cost
thereof.
A single system possesses these capabilities due to the selectively
adaptable input means 115 and A/D means 118, the frequency-agile
module transmitter 127 and base transmitter 116, and the
programmable module microcontroller 121 and EEPROM 124. One
universal platform design then can be utilized for all
applications. In addition, the signal processing module 85 can
comprise multiple copies of the input means 115 and the A/D means
118. Cost savings can be achieved by multiplexing at several
different points in the input means 115 and the A/D means 118
allowing hardware to be shared among external inputs 88.
After receipt by the input means 115, the external input 88 is
inputted to the A/D means 118. The A/D means 118 converts the input
to a digital signal 142 and conditions it. The A/D means 118
utilizes at least one programmable A/D converter. This programmable
A/D converter may be an AD7714 as manufactured by Analog Devices or
similar. Depending upon the application, the input means 115 may
also include at least one low noise differential preamp. This
preamp may be an INA126 as manufactured by Burr-Brown or similar.
The module microcontroller 121 can be programmed to control the
input means 115 and the A/D means 118 to provide specific number of
external inputs 88, sampling rate, filtering and gain. These
parameters are initially configured by programming the module
microcontroller 121 to control the input means 115 and the A/D
means 118 via input communications line 145 and A/D communications
line 148 based upon the input characteristics and the particular
application. If different sensors are used, the A/D converter is
reconfigured by reprogramming the module microcontroller 121. In
this manner, the input means 115 and the A/D means 118 can be
configured to accept analog inputs of 4-20 mA, +/-5 volts, +/-15
volts or a range from +/-microvolts to millivolts. They also can be
configured to accept digital inputs for digital applications such
as detection of contact closure.
The module microcontroller 121 controls the operation of the signal
processing module 85. In the present invention, the module
microcontroller 121 includes a serial EEPROM 124 but any
nonvolatile memory (or volatile memory if the signal processing
module remains powered) can be used. The EEPROM 124 can also be a
separate component external to the module microcontroller 121.
Advantageously, the module microcontroller 121 may be PIC16C74A
PIC16C74B or a PIC16C77 both manufactured by MicroChip, or an Amtel
AT90S8515 or similar. The module microcontroller may advantageously
contain two microprocessors in series as shown in FIG. 5. The
module microcontroller 121 is programmed by the external
programming means 106 (shown in FIG. 4) through the connector 172
or through radio frequency signal from the base station 97 (shown
in FIG. 4). The same module microcontroller 121, therefore, can be
utilized for all applications and inputs by programming it for
those applications and inputs. If the application or inputs change,
the module microcontroller 121 is modified by merely reprogramming.
The digital signal 142 is inputted to the module microcontroller
121. The module microcontroller 121 formats the digital signal 142
into a digital data stream 151 encoded with the data from the
digital signal 142. The digital data stream 151 is composed of data
bytes corresponding to the encoded data and additional data bytes
to provide error correction and housekeeping functions.
Advantageously, the digital data stream 151 is organized in data
packets with the appropriate error correction data bytes
coordinated on a per data packet basis. These packets can
incorporate data from a single input channel or from several input
channels in a single packet, or for some applications may
advantageously include several temporally differing measurements of
one or a plurality of input channels in a single packet. The
digital data stream 151 is used to modulate the carrier frequency
generated by the transmitter 127.
The module transmitter 127 is under module microcontroller 121
control. The module transmitter 127 employs frequency synthesis to
generate the carrier frequency. In the preferred embodiment, this
frequency synthesis is accomplished by a voltage controlled crystal
reference oscillator and a voltage controlled oscillator in a phase
lock loop circuit. The digital data stream 151 is used to frequency
modulate the carrier frequency resulting in the radio frequency
signal 94 which is then transmitted through the module antenna 100.
The generation of the carrier frequency is controlled by the module
microcontroller 121 through programming in the EEPROM 124, making
the module transmitter 127 frequency agile over a broad frequency
spectrum. In the United States and Canada a preferred operating
band for the carrier frequency is 902 to 928 MHz. The EEPROM 124
can be programmed such that the module microcontroller 121 can
instruct the module transmitter 127 to generate a carrier frequency
in increments between 902 to 928 MHz. as small as about 5 to 10
kHz. In the US and other countries of the world, the carrier
frequency may be in the 902-928 MHz, Wireless Medical Telemetry
Bands (WMTS), 608-614 MHz, 1395-1400 MHz, or 1429-1432 MHz or other
authorized band. This allows the system to be usable in non-North
American applications and provides additional flexibility.
The voltage controlled crystal oscillator (not shown) in the module
transmitter 127, not only provides the reference frequency for the
module transmitter 127 but, advantageously also provides the clock
function 154 for the module microcontroller 121 and the A/D means
118 assuring that all components of the signal processing module 85
are synchronized. An alternate design can use a plurality of
reference frequency sources where this arrangement can provide
certain advantages such as size or power consumption in the
implementation.
The module receiver 133 in the signal processing module 85 receives
RF signals from the base station 97 (shown in FIG. 4). The signals
from the base station 97 can be used to operate and control the
signal processing module 85 by programming and reprogramming the
module microprocessor 121 and EEPROM 124 therein.
Referring now to FIG. 6, the base station 97 has a base antenna 103
through which RF signals 94 are received. Base microcontroller 160
controls the operation of the base station 97 including base
receiver 163, base transmitter 166, and base power supply 169. Base
receiver 163 receives the RF signal 94 from base antenna 103. The
base receiver 163 demodulates the RF signal 94 and the base
microcontroller 160 removes any error correction and performs other
housekeeping tasks. The data is then downloaded through connector
112 to the external programming means 106 (shown in FIG. 4) or
other personal computer (PC) or data storage/viewing device for
viewing in real time, storage, or analysis, or is downloaded to
removable memory of some form.
FIG. 7 is a schematic diagram of a multi-task monitoring system. In
FIG. 7, a patient or subject is shown having the neurological 200,
cardiac 202, muscular 204, and other environmental conditions 206
measured by sensors (not shown) and input into four separate data
acquisition units 210, 212, 214, and 216. In this example, each
unit 210, 212, 214, and 216 can accept up to 32 inputs. The units
transmit signals 220, 222, 224, and 226 at different wireless radio
frequencies from their respective antennas 228. The signals 220,
222, 224, and 226 do not interfere with each other because they
have been manually or automatically selected to reduce interference
as described earlier in the application. The signals can be
received 232 simultaneously or in some ordered fashion by the
antenna 230 on the receiving unit 234. The receiving unit 234 is
both data and electrically connected via a USB connection 236 to a
main processor or computer 238. The physiological signals are then
processed or further processed by the computer 238, depending on
whether processing took place in the data acquisition units 210,
212, 214, and 216. The information or data from the computer 238
can be output to a monitor 240 and/or into a data file 242.
FIG. 8 is a diagram of an artifact rejection module 250 that can be
used in either the in-home data acquisition system (not shown) or a
computer or processor (not shown) linked to the data acquisition
unit of the present invention. In FIG. 8, a subject's EEG signal
252 is preferably continuously fed 254 into artifact rejection
algorithms within the data acquisition unit processor.
Simultaneously sensor signals 260 from the subject's movement or
motion are also fed into the artifact rejection processor so the
EEG signal can be corrected 262 for effects of abnormal or
prejudicial motion by the subject. The sensors for determining the
subject's motion are described above, but the most preferred is an
accelerometer that is incorporated into the EEG data acquisition
unit itself.
It will be apparent to those skilled in the art that various
modifications and variations can be made to the present invention
without departing from the spirit and scope of the invention. Thus,
it is intended that the present invention cover the modifications
and variations of this invention provided they come within the
scope of the appended claims and their equivalents.
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